A survey of explainable artificial intelligence in healthcare: Concepts, applications, and challenges
Ibomoiye Domor Mienye, George Obaido, Nobert Jere, Ebikella Mienye, Kehinde Aruleba, Ikiomoye Douglas Emmanuel, Blessing Ogbuokiri
Abstract
Explainable AI (XAI) has the potential to transform healthcare by making AI-driven medical decisions more transparent, reliable, and ethically compliant. Despite its promise, the healthcare sector faces several challenges, including the need to balance interpretability and accuracy, integrating XAI into clinical workflows, and ensuring adherence to rigorous regulatory standards. This paper provides a comprehensive review of XAI in healthcare, covering techniques, challenges, opportunities, and advancements, thereby enhancing the understanding and practical application of XAI in healthcare. The study also explores responsible AI in healthcare, discussing new perspectives and emerging trends, offering valuable insights for researchers and practitioners. The insights and recommendations presented aim to guide future research and policy-making, fostering the development of transparent, trustworthy, and effective AI-driven solutions.